Date of Publication

8-8-2022

Document Type

Bachelor's Thesis

Degree Name

Bachelor of Science in Premed Physics

Subject Categories

Physics

College

College of Science

Department/Unit

Physics

Thesis Advisor

Rene C. Batac

Defense Panel Chair

Ma. Cecilia D. Galvez

Defense Panel Member

Ma. Cecilia D. Galvez
Prane Mariel B. Ong
Ofelia T. Rempillo

Abstract (English)

Air Pollution has caused many problems worldwide, specifically one’s surrounding environment and health. This is due to the numerous contaminants that surround the air. Thus that being said, researchers and government leaders attempt to find solutions on how to tackle the aforementioned phenomenon. In this paper, the distribution of the annual PM2.5 concentrations of countries and territories as reported by the World Health Organization (WHO) for the last decade using self-reported data from governments and other contributing institutions is studied. Aside from the WHO, the study also utilized the IQAir website for data collection of PM2.5 concentrations given by various contributors and IQAir AI data modeling. In order to tackle the analysis of the distribution after collecting data, the code application, Spyder, containing the process of logarithmic binning and plotting of points in a probability distribution graph based on the PM2.5 concentrations of each category was run. The resulting distributions follow various regimes corresponding to the low, intermediate, and high PM2.5 concentrations. The intermediate regime is fitted with a power-law with a scaling exponent of 2.44 and explained from a complexity perspective using a truncated exponential growth model with random truncation growth rates. From there, it was observed that most graphs from each category follow the power law distribution. The self-organization resulting from the interplay between natural and human-induced factors in the atmosphere is deemed to persist despite the gradual evolution of the actual statistical manifestations.

Abstract Format

html

Abstract (Filipino)

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Abstract Format

html

Language

English

Format

Electronic

Keywords

Air—Pollution—Measurement

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Embargo Period

8-31-2023

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